Gravity core

Search Relevance Field

let search results settle by relevance, confidence, and recency

Running the actual pattern live via applyPattern() — switch the substrate, stack overlays, watch the signals, or reverse the dynamics. Not a mock.

"Search Relevance Field" — let search results settle by relevance, confidence, and recency. It has a attract layer (draw matter into a focus / well), a memory layer (a decaying trail / hysteresis), and a repel layer (carve a void / keep-clear region). The active render stack is particles, heatmap.

Relevance becomes attract strength so confident results sink into deeper wells; weak results drift out (repel); previously opened results retain memory.

Runtime tokens: attract draw matter into a focus / wellmemory a decaying trail / hysteresisrepel carve a void / keep-clear region
Concepts: relevance
Metrics: density a semantic lane — drive it with data-field-<metric> (or a domain model); without that its --field-<metric> stays inertmemory computed every frame by the platform (proximity · engagement · relationships · age)recency computed every frame by the platform (proximity · engagement · relationships · age) density is a host-supplied lane — drive it with data-field-<metric> (or a domain model); without that, its --field-* stays inert.
Diagnostics: potential prediction heatmap
Conditions: related
Render: particles · heatmap
Reduced motion: results re-rank into a static ordered list; memory shows as a "seen" tick
Without motion: ranking is a numbered list; relevance and recency are labelled

Copy this pattern

<field-root></field-root>
  <div data-body="attract" data-strength="1" data-range="280" data-feedback></div>
  <div data-body="memory" data-strength="0.6" data-range="320"></div>
  <div data-body="repel" data-strength="0.5" data-range="200"></div>

<script type="module">
  import '@fundamental-engine/elements';
</script>

<field-root></field-root>
  <div data-body="attract" data-strength="1" data-range="280" data-feedback></div>
  <div data-body="memory" data-strength="0.6" data-range="320"></div>
  <div data-body="repel" data-strength="0.5" data-range="200"></div>

import { FieldField } from '@fundamental-engine/react';

export default function SearchRelevanceField() {
  return (
    <FieldField>
      <div data-body="attract" data-strength="1" data-range="280" data-feedback />
      <div data-body="memory" data-strength="0.6" data-range="320" />
      <div data-body="repel" data-strength="0.5" data-range="200" />
    </FieldField>
  );
}

{
  "id": "search-relevance-field",
  "name": "Search Relevance Field",
  "intent": "let search results settle by relevance, confidence, and recency",
  "naturalField": "gravity",
  "primitives": [
    "attract",
    "memory",
    "repel"
  ],
  "bodies": [
    {
      "body": "attract",
      "strength": 1,
      "range": 280,
      "feedback": true
    },
    {
      "body": "memory",
      "strength": 0.6,
      "range": 320
    },
    {
      "body": "repel",
      "strength": 0.5,
      "range": 200
    }
  ],
  "render": [
    "particles",
    "heatmap"
  ],
  "metrics": [
    "density",
    "memory",
    "recency"
  ],
  "diagnostics": [
    "potential",
    "prediction",
    "heatmap"
  ],
  "accessibility": {
    "reducedMotion": "results re-rank into a static ordered list; memory shows as a \"seen\" tick",
    "meaningWithoutMotion": "ranking is a numbered list; relevance and recency are labelled"
  },
  "notes": "Relevance becomes attract strength so confident results sink into deeper wells; weak results drift out (repel); previously opened results retain memory.",
  "tier": "core",
  "status": "shipped",
  "concepts": [
    "relevance"
  ],
  "conditions": [
    "related"
  ]
}

Copy this pattern

See also